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학술저널
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한국멀티미디어학회 멀티미디어학회논문지 JOURNAL OF KOREA MULTIMEDIA SOCIETY Vol.9 No.12
발행연도
2006.12
수록면
1,529 - 1,541 (13page)

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Moving objects have been widely employed in traffic and logistic applications. Spatio-temporal aggregations mainly describe the moving object's behavior in the spatial data warehouse. The previous works usually express the object moving in some certain region, but ignore the object often moving along as the trajectory. Other researches focus on aggregation and comparison of trajectories. They divide the spatial region into units which records how many times the trajectories passed in the unit time. It not only makes the storage space quite ineffective, but also can not maintain spatial data property. ln this paper, a spatio-temporal aggregation index structure for moving object trajectory in constrained network is proposed. An extended B-tree node contains the information of timestamp and the aggregation values of trajectories with two directions. The network is divided into segments and then the spatial index structure is constructed. There are the leaf node and the non leaf node. The leaf node contains the aggregation values of moving object's trajectory and the pointer to the extended B-tree. And the non leaf node contains the MER (Minimum Bounding Rectangle), MSAV (Max Segment Aggregation Value) and its segment ill. The proposed technique overcomes previous problems efficiently and makes it practicable finding moving object trajectory in the time interval. It improves the shortcoming of R-tree, and makes some improvement to the spatio-temporal data in query processing and storage.

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ABSTRACT
1. INTRODUCTION
2. RELATED WORKS
3. aCN-RB TREE CONSTRUCTION
4. PERFORMANCE EVALUATION
5. CONCLUSIONS
6. REFERENCE

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